Concurrent Programming with Multi-Agents and the Chemical Abstract Machine

2011 ◽  
pp. 26-47
Author(s):  
Wanli Ma ◽  
Dat Tran
Keyword(s):  
Computational Model ◽  
Programming Language ◽  
Concurrent Programming ◽  
Theoretical Background ◽  
Programming Approach ◽  
Chemical Abstract ◽  
Abstract Machine ◽  
Multi Agent ◽  
Reactive Programming ◽  
Multi Agents

In this chapter, we propose a new concurrent programming approach called MACH (multi-agent extended chemical abstract machine). MACH extends the chemical abstract machine with multiple coexisting agents. This paper focuses on the design, implementation, and verification of MACH. The aim of MACH is to develop a reactive programming language based on an interactive computational model, which we believe is the key to concurrent programming. We present MACH as a simple and efficient programming approach based on a sound theoretical background.

Causal-Consistent Replay Reversible Semantics for Message Passing Concurrent Programs

2021 ◽  
Vol 178 (3) ◽  
pp. 229-266
Author(s):  
Ivan Lanese ◽  
Adrián Palacios ◽  
Germán Vidal
Keyword(s):  
Programming Language ◽  
Message Passing ◽  
Concurrent Programming ◽  
Concurrent Systems ◽  
Concurrent Programs ◽  
Unified Framework ◽  
Innovative Technique ◽  
Dual Notion

Causal-consistent reversible debugging is an innovative technique for debugging concurrent systems. It allows one to go back in the execution focusing on the actions that most likely caused a visible misbehavior. When such an action is selected, the debugger undoes it, including all and only its consequences. This operation is called a causal-consistent rollback. In this way, the user can avoid being distracted by the actions of other, unrelated processes. In this work, we introduce its dual notion: causal-consistent replay. We allow the user to record an execution of a running program and, in contrast to traditional replay debuggers, to reproduce a visible misbehavior inside the debugger including all and only its causes. Furthermore, we present a unified framework that combines both causal-consistent replay and causal-consistent rollback. Although most of the ideas that we present are rather general, we focus on a popular functional and concurrent programming language based on message passing: Erlang.

scholarly journals A Programming Approach to Collective Autonomy

2021 ◽  
Vol 10 (2) ◽  
pp. 27
Author(s):  
Roberto Casadei ◽  
Gianluca Aguzzi ◽  
Mirko Viroli
Keyword(s):  
Autonomous Vehicles ◽  
Autonomic Computing ◽  
Autonomous Agents ◽  
Programming Approach ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Multi Agent ◽  
Simulated Case ◽  
Complex Settings

Research and technology developments on autonomous agents and autonomic computing promote a vision of artificial systems that are able to resiliently manage themselves and autonomously deal with issues at runtime in dynamic environments. Indeed, autonomy can be leveraged to unburden humans from mundane tasks (cf. driving and autonomous vehicles), from the risk of operating in unknown or perilous environments (cf. rescue scenarios), or to support timely decision-making in complex settings (cf. data-centre operations). Beyond the results that individual autonomous agents can carry out, a further opportunity lies in the collaboration of multiple agents or robots. Emerging macro-paradigms provide an approach to programming whole collectives towards global goals. Aggregate computing is one such paradigm, formally grounded in a calculus of computational fields enabling functional composition of collective behaviours that could be proved, under certain technical conditions, to be self-stabilising. In this work, we address the concept of collective autonomy, i.e., the form of autonomy that applies at the level of a group of individuals. As a contribution, we define an agent control architecture for aggregate multi-agent systems, discuss how the aggregate computing framework relates to both individual and collective autonomy, and show how it can be used to program collective autonomous behaviour. We exemplify the concepts through a simulated case study, and outline a research roadmap towards reliable aggregate autonomy.

scholarly journals Instrumentation des activités des tuteurs à l’aide d’un système multi-agents d’analyse automatique des interactions

2011 ◽  
Vol Volume 14 - 2011 - Special... ◽  
Author(s):  
Ilham Oumaira ◽  
Rochdi Messoussi ◽  
Raja TOUAHNI
Keyword(s):  
Nous Avons ◽  
Social Cognitive ◽  
Adaptive System ◽  
Interaction Analysis ◽  
Interaction Data ◽  
Multi Agent System ◽  
Système Adaptatif ◽  
International Audience ◽  
Multi Agent ◽  
Multi Agents

International audience Research presented in this article is dedicated to the tutor instrumentation in distance collaborative learning situations. We are particularly interested in the reuse of interaction analysis indicators. In this paper, we present our system SYSAT; a multi-agent system for monitoring the activities of learners. The aim of SYSAT is to reuse indicators (social, cognitive, emotional ...) reported in the literature, in an open and adaptive system. We tested our system on the interaction data from two experiments conducted with two master students of the Ibn Tofail University. The article presents the results and discusses the prospects for Research. Ce travail s'inscrit dans le cadre des recherches sur les Environnements Informatiques pour l'Apprentissage Humain (EIAH), et plus particulièrement dans l’assistance du tuteur dans le suivi des apprenants lors des activités d’apprentissage collaboratives en ligne. Cet article décrit l’architecture du système SYSAT, un système multi-agents d’analyse automatique des interactions. L’objectif de SYSAT est de réutiliser les indicateurs (sociaux, cognitifs, affectifs…) rapportés dans la littérature, au sein d’un système adaptatif et ouvert. Nous avons testé notre système sur les données d’interactions issues de deux expérimentations menées avec les étudiants de deux masters à l’université Ibn Tofail. L’article présente les résultats obtenus et évoque les perspectives de recherche.

scholarly journals From Interpreter to Logic Engine by Defunctionalization

2003 ◽  
Vol 10 (25) ◽  
Author(s):  
Dariusz Biernacki ◽  
Olivier Danvy
Keyword(s):  
Logic Programming ◽  
Programming Language ◽  
Operational Semantics ◽  
Lambda Calculus ◽  
Transition System ◽  
Abstract Machine ◽  
Logic Programming Language ◽  
Delimited Continuations ◽  
Simple Logic ◽  
Control Operators

Starting from a continuation-based interpreter for a simple logic programming language, propositional Prolog with cut, we derive the corresponding logic engine in the form of an abstract machine. The derivation originates in previous work (our article at PPDP 2003) where it was applied to the lambda-calculus. The key transformation here is Reynolds's defunctionalization that transforms a tail-recursive, continuation-passing interpreter into a transition system, i.e., an abstract machine. Similar denotational and operational semantics were studied by de Bruin and de Vink in previous work (their article at TAPSOFT 1989), and we compare their study with our derivation. Additionally, we present a direct-style interpreter of propositional Prolog expressed with control operators for delimited continuations.<br /><br />Superseded by BRICS-RS-04-5.

scholarly journals Developing fire evacuation simulation through BDI-based modelling and simulation

2021 ◽  
Vol 2107 (1) ◽  
pp. 012047
Author(s):  
Ng YenChern ◽  
Cheah WaiShiang ◽  
Sim KengWai ◽  
Muhammad Asyraf bin Khairuddin ◽  
Nurfauza bt Jali ◽  
...  
Keyword(s):  
Multi Agent System ◽  
Game Engine ◽  
Evacuation Simulation ◽  
System A ◽  
Bdi Agent ◽  
Fire Evacuation ◽  
Multi Agent ◽  
Main Components ◽  
Multi Agents

Abstract Fire evacuation simulation is used to simulate the fire evacuation procedures by involving human-like agents. In this paper, the fire evacuation simulation is designed and developed by adopting the BDI agent plug-in. BDI (Belief, Desires, Intentions) is a technique used in modelling the multi-agent system. A tool and BDI methodology are introduced to help in modelling human behaviour and the decision making of an agent. In this paper, the usability of the BDI methodology and BDI agent plug-in tool is studied through a case study of a fire evacuation environment. The case study covers the three main components needed in a fire evacuation simulation: the fire (the spread of the fire and smoke), the building layout (the classroom and physical objects), and the human-like multi-agents. Using the Unity game engine, a fire evacuation simulation system is built based on the requirements, methodology, and design. The usability of the BDI agent plug-in tool can be proven by observing the results of the fire evacuation simulation and the reaction of agents when encountering the fire situation. However, there are also some limitations of this fire evacuation simulation. Therefore, there are works to be done to develop a more realistic fire evacuation simulation and more human-like multi-agents in future.

Approach for Negotiation Problems in Multi-Agent Systems for DC Micro Grid Using Multi-Objective Evolutionary Algorithms

2015 ◽  
Vol 713-715 ◽  
pp. 2106-2109
Author(s):  
Mauricio Mauledoux ◽  
Edilberto Mejía-Ruda ◽  
Oscar I. Caldas
Keyword(s):  
Genetic Algorithms ◽  
Evolutionary Algorithms ◽  
Pareto Optimal ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Multi Objective ◽  
Multi Agent ◽  
Micro Grid ◽  
Optimal Space ◽  
Multi Agents

The work is devoted to solve allocation task problem in multi agents systems using multi-objective genetic algorithms and comparing the technique with methods used in game theories. The paper shows the main advantages of genetic algorithms and the way to apply a parallel approach dividing the population in sub-populations saving time in the search and expanding the coverage of the solution in the Pareto optimal space.

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